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Principal Data Scientist - Remote

Minnetonka, Minnesota

Pay
$112,700–193,200/year — pay source
*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 - $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
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Work setup
Unconfirmed
Employment
Unconfirmed
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What you’ll work on

Full posting

We are seeking a seasoned Principal Data Scientist to lead the design, development, and deployment of advanced machine learning and generative AI solutions.

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.

  • Lead solution architecture and hands-on development of machine learning and generative AI applications to solve complex business challenges

  • Collaborate with data engineers, software engineers, product managers, and cross-functional teams to translate business requirements into re-usable, production-ready capabilities

  • Document architecture designs, conduct thorough technical design reviews, and present proposals and findings to key stakeholders

From the employer’s posting
We are seeking a seasoned Principal Data Scientist to lead the design, development, and deployment of advanced machine learning and generative AI solutions. In this role, you will define end-to-end ML architectures, select appropriate tools and frameworks, drive innovative proof-of-concept experiments, and guide engineering teams in productionizing scalable AI services. With a focus on responsible AI practices, you will design and build production-grade solutions while providing technical guidance and mentorship to junior engineers. A solid foundation in statistical methods, deep learning, generative AI, cloud expertise, and solid communication skills are essential to driving high-impact technology initiatives across the enterprise.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.
Primary Responsibilities: Lead solution architecture and hands-on development of machine learning and generative AI applications to solve complex business challenges Design, build, and deploy scalable, production-grade AI solutions using traditional ML, deep learning, and modern LLM-based approaches with an emphasis on responsible AI principles, fairness, transparency, and accountability
Provide technical guidance, code reviews, and mentorship to junior engineers to foster technical excellence without formal people management responsibilities Collaborate with data engineers, software engineers, product managers, and cross-functional teams to translate business requirements into re-usable, production-ready capabilities Document architecture designs, conduct thorough technical design reviews, and present proposals and findings to key stakeholders
Collaborate with data engineers, software engineers, product managers, and cross-functional teams to translate business requirements into re-usable, production-ready capabilities Document architecture designs, conduct thorough technical design reviews, and present proposals and findings to key stakeholders You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

What you’ll bring

All qualifications

Core experience

  • 10+ years of experience designing, building, and deploying production machine learning solutions
  • 3+ years of recent experience building GenAI applications using LLMs and frameworks such as LangChain and/or LangGraph
  • Demonstrated experience defining cloud-native ML infrastructure, containerization (Docker/Kubernetes), ML pipelines, and MLOps (CI/CD, model registry, monitoring) on at least one major cloud platform (AWS, Azure, or GCP)
  • Deep expertise in core ML and statistical methods (supervised/unsupervised learning, regression, classification, clustering, time series, Bayesian modeling) and deep domain expertise in either NLP or Computer Vision with hands-on solution ownership

Preferred experience

  • Experience working with healthcare data, systems, or use cases within US-based healthcare or enterprise environments
  • Experience with MLOps tools such as MLflow, Kubeflow, TFX, Airflow, or equivalent
  • Familiarity with big data technologies such as Apache Spark, Hadoop, or Dask
  • Knowledge of data visualization and dashboarding tools (eg, Tableau, Power BI)
Qualification wording
10+ years of experience designing, building, and deploying production machine learning solutions
3+ years of recent experience building GenAI applications using LLMs and frameworks such as LangChain and/or LangGraph
Demonstrated experience defining cloud-native ML infrastructure, containerization (Docker/Kubernetes), ML pipelines, and MLOps (CI/CD, model registry, monitoring) on at least one major cloud platform (AWS, Azure, or GCP)
Deep expertise in core ML and statistical methods (supervised/unsupervised learning, regression, classification, clustering, time series, Bayesian modeling) and deep domain expertise in either NLP or Computer Vision with hands-on solution ownership
Experience working with healthcare data, systems, or use cases within US-based healthcare or enterprise environments
Experience with MLOps tools such as MLflow, Kubeflow, TFX, Airflow, or equivalent
Familiarity with big data technologies such as Apache Spark, Hadoop, or Dask
Knowledge of data visualization and dashboarding tools (eg, Tableau, Power BI)

Tools in this posting

  • Python
  • AWS
  • Azure
  • Hadoop
  • MLflow
  • Spark
  • Tableau
  • Airflow
  • PyTorch
  • TensorFlow
  • Google Cloud (GCP)
  • Power BI
  • Docker
  • Kubernetes
  • Keras
  • Dask
Source — Tool mentions in context
- Solid background in traditional ML and deep learning demonstrated through substantive work prior to or alongside recent GenAI efforts - Hands-on programming proficiency in Python and deep learning frameworks (eg, PyTorch, TensorFlow, Keras) - Solid foundation in probability, linear algebra, and statistical inference with a proven track record of moving models from research/POC into production at scale
- 3+ years of recent experience building GenAI applications using LLMs and frameworks such as LangChain and/or LangGraph - Demonstrated experience defining cloud-native ML infrastructure, containerization (Docker/Kubernetes), ML pipelines, and MLOps (CI/CD, model registry, monitoring) on at least one major cloud platform (AWS, Azure, or GCP) - Deep expertise in core ML and statistical methods (supervised/unsupervised learning, regression, classification, clustering, time series, Bayesian modeling) and deep domain expertise in either NLP or Computer Vision with hands-on solution ownership
- Experience with MLOps tools such as MLflow, Kubeflow, TFX, Airflow, or equivalent - Familiarity with big data technologies such as Apache Spark, Hadoop, or Dask - Knowledge of data visualization and dashboarding tools (eg, Tableau, Power BI)
- Experience working with healthcare data, systems, or use cases within US-based healthcare or enterprise environments - Experience with MLOps tools such as MLflow, Kubeflow, TFX, Airflow, or equivalent - Familiarity with big data technologies such as Apache Spark, Hadoop, or Dask
- Familiarity with big data technologies such as Apache Spark, Hadoop, or Dask - Knowledge of data visualization and dashboarding tools (eg, Tableau, Power BI) Location

Job description

View original posting ↗

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.

 

Position Summary

We are seeking a seasoned Principal Data Scientist to lead the design, development, and deployment of advanced machine learning and generative AI solutions. In this role, you will define end-to-end ML architectures, select appropriate tools and frameworks, drive innovative proof-of-concept experiments, and guide engineering teams in productionizing scalable AI services. With a focus on responsible AI practices, you will design and build production-grade solutions while providing technical guidance and mentorship to junior engineers. A solid foundation in statistical methods, deep learning, generative AI, cloud expertise, and solid communication skills are essential to driving high-impact technology initiatives across the enterprise.

 

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.

 

For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

 

Primary Responsibilities:

  • Lead solution architecture and hands-on development of machine learning and generative AI applications to solve complex business challenges
  • Design, build, and deploy scalable, production-grade AI solutions using traditional ML, deep learning, and modern LLM-based approaches with an emphasis on responsible AI principles, fairness, transparency, and accountability
  • Drive proof-of-concept experiments in generative AI (transformers, GANs, diffusion models) and evaluate emerging research, tools, and trends to inform strategic innovation and technical design
  • Establish best practices for model governance, versioning, reproducibility, security, and integration with enterprise architectural standards
  • Provide technical guidance, code reviews, and mentorship to junior engineers to foster technical excellence without formal people management responsibilities
  • Collaborate with data engineers, software engineers, product managers, and cross-functional teams to translate business requirements into re-usable, production-ready capabilities
  • Document architecture designs, conduct thorough technical design reviews, and present proposals and findings to key stakeholders

 

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

  • 10+ years of experience designing, building, and deploying production machine learning solutions
  • 3+ years of recent experience building GenAI applications using LLMs and frameworks such as LangChain and/or LangGraph
  • Demonstrated experience defining cloud-native ML infrastructure, containerization (Docker/Kubernetes), ML pipelines, and MLOps (CI/CD, model registry, monitoring) on at least one major cloud platform (AWS, Azure, or GCP)
  • Deep expertise in core ML and statistical methods (supervised/unsupervised learning, regression, classification, clustering, time series, Bayesian modeling) and deep domain expertise in either NLP or Computer Vision with hands-on solution ownership
  • Solid background in traditional ML and deep learning demonstrated through substantive work prior to or alongside recent GenAI efforts
  • Hands-on programming proficiency in Python and deep learning frameworks (eg, PyTorch, TensorFlow, Keras)
  • Solid foundation in probability, linear algebra, and statistical inference with a proven track record of moving models from research/POC into production at scale
  • Proven problem-solving ability and excellent verbal and written communication skills

 

Preferred Qualifications

  • Experience working with healthcare data, systems, or use cases within US-based healthcare or enterprise environments
  • Experience with MLOps tools such as MLflow, Kubeflow, TFX, Airflow, or equivalent
  • Familiarity with big data technologies such as Apache Spark, Hadoop, or Dask
  • Knowledge of data visualization and dashboarding tools (eg, Tableau, Power BI)

 

Location

  • Preference for candidates based in Minnesota (office-based)
  • Solid US-based candidates in other locations may be considered for remote work

 

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy

 

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 - $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.

 

Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

 

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.  

 

 

UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

 

UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.  

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on careers.unitedhealthgroup.com. The employer’s form will show what is required.

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Source & posting history

View original posting ↗

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Pay
*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 - $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
Location & working pattern

Minnetonka, Minnesota

- Preference for candidates based in Minnesota (office-based) - Solid US-based candidates in other locations may be considered for remote work *All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Oct 8, 2026
Recorded sightings
8
Last seen by us
Oct 9, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

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